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Using statistical process control to make data-based clinical decisions

A Pfadt¹, D J Wheeler

¹New York State Institute for Basic Research in Developmental Disabilities, Staten Island 10314, USA.

Journal of Applied Behavior Analysis

|January 1, 1995

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Applied behavior analysis uses data to understand behavior. Statistical process control (SPC) offers tools for continuous improvement in human services, enhancing client outcomes.

Area of Science:

Behavioral Science
Industrial-Organizational Psychology

Background:

Applied behavior analysis (ABA) traditionally analyzes behavior through antecedents, behavior, and consequences.
Empirical evaluation of hypotheses and data-based clinical decisions are central to ABA.

Observation:

This paper explores Statistical Process Control (SPC), a quality control method from industrial engineering.
SPC, developed by Shewhart and Deming, focuses on continual improvement and customer satisfaction.

Findings:

SPC utilizes tools like control charts and Pareto charts for data analysis.
Integrating SPC into human service organizations can drive continuous improvement in client functioning.
Examples demonstrate SPC's application in analyzing behavioral data.

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Implications:

SPC offers a novel approach to analyzing variability in behavioral data.
Adoption of SPC can enhance data-based clinical decision-making.
Creating a supportive organizational climate is crucial for routine SPC implementation.